{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 两根史诗级K线：检验100年来那些“交易天才” . 第4讲"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 本段代码展示了利用Numpy生成正态分布随机收益率序列，模拟股票K线的过程"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. 环境设置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 每年交易日个数\n",
    "DAYS_PER_YEAR = 242\n",
    "# 每天5分钟线个数\n",
    "PERIODS_PER_DAY = int(240 / 5)\n",
    "# 转换为百分比所需倍数\n",
    "TO_PERCENT = 100.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. 分钟线模拟生成函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_price_5m(annu_ret, annu_vol, n=DAYS_PER_YEAR):\n",
    "    \"\"\"Return price array of freq = 5Min\"\"\"\n",
    "    ratio = DAYS_PER_YEAR * PERIODS_PER_DAY\n",
    "    vol_5m = annu_vol *1. / np.sqrt(ratio)\n",
    "    alpha_5m = annu_ret *1. / (ratio)\n",
    "    \n",
    "    ret = np.random.randn(n * PERIODS_PER_DAY) * vol_5m + alpha_5m\n",
    "    price = np.cumprod(1+ret)\n",
    "    return price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_ohlc(arr, t):\n",
    "    \"\"\"\n",
    "    Get OHLC price from array of price 'arr'.\n",
    "    \n",
    "    \"\"\"\n",
    "    return t, arr[0], arr.max(), arr.min(), arr[-1]\n",
    "\n",
    "def get_quotes(price_arr, sub_length):\n",
    "    \"\"\"\n",
    "    Construt OHLC price of each period of length 'sub_length' from 'price_arr'\n",
    "    \n",
    "    \"\"\"\n",
    "    quotes = []\n",
    "    for i in range(0, len(price_arr), sub_length):\n",
    "        sub_arr = price_arr[i: i + sub_length]\n",
    "        quote = get_ohlc(sub_arr, i // sub_length)\n",
    "        quotes.append(quote)\n",
    "    return quotes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. 作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\QuantosTerminal\\python\\lib\\site-packages\\matplotlib\\cbook\\deprecation.py:106: MatplotlibDeprecationWarning: The finance module has been deprecated in mpl 2.0 and will be removed in mpl 2.2. Please use the module mpl_finance instead.\n",
      "  warnings.warn(message, mplDeprecation, stacklevel=1)\n"
     ]
    }
   ],
   "source": [
    "from matplotlib.finance import candlestick_ohlc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x4f53d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 指定不同K线的年化收益率与年化波动率\n",
    "alpha_vol_list = [\n",
    "    {'alpha': 0.0 , 'volatility': 0.30},\n",
    "    {'alpha': 0.05, 'volatility': 0.30},\n",
    "    {'alpha': 0.45, 'volatility': 0.30},\n",
    "]\n",
    "n_subfigures = len(alpha_vol_list)\n",
    "n_days = 242  # 要画多少个交易日的K线\n",
    "\n",
    "fig, axes = plt.subplots(n_subfigures, 1, figsize=(16, 6 * n_subfigures))\n",
    "\n",
    "for i in range(n_subfigures):\n",
    "    alpha = alpha_vol_list[i]['alpha']\n",
    "    vol = alpha_vol_list[i]['volatility']\n",
    "    ax = axes[i]\n",
    "    \n",
    "    price_5m = get_price_5m(alpha, vol, n_days)  # 计算价格序列\n",
    "    quotes = get_quotes(price_5m, sub_length=PERIODS_PER_DAY)  # 计算quote序列\n",
    "    \n",
    "    candlestick_ohlc(ax=ax, quotes=quotes, colorup='red', colordown='green')  # 做蜡烛图\n",
    "    \n",
    "    ax.set(xlabel='Days', ylabel='Net Value',  # 横轴纵轴名\n",
    "           ylim=(0.6, 2.0),                    # 纵轴范围\n",
    "           title='Annual Alpha {:.0f}%; Annual Volatility {:.0f}%'.format(alpha*TO_PERCENT, vol*TO_PERCENT))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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